Rutgers FinTech Bootcamp
Issued by
Rutgers University
The Rutgers FinTech Bootcamp takes a multidisciplinary approach to finance, programming, data analysis, and modern tools in cryptocurrency and blockchain. Earner demonstrated proficiencies in using Python and financial fundamentals to model future financial performance; building an Ethereum blockchain with an understanding of how transactions are validated on a distributed ledger; and evaluating the strengths and disadvantages of machine learning algorithms within the field of finance.
- Type Validation
- Level Foundational
- Time Months
- Cost Paid
Skills
- Algorithmic Trading
- Amazon Web Services
- APIs
- Consensus Algorithms Transactions
- Cryptocurrency
- Distributed Ledger
- Ethereum
- Financial Modeling
- Financial Ratios
- Forecasting
- Ganache
- K-Means Clustering
- K-Nearest Neighbors
- Linear Regression
- Logistic Regression
- Matplotlib
- Mining
- Neural Networks
- NumPy
- Pandas
- Python
- Random Forests
- Scikit-learn
- SciPy
- Smart Contracts
- Solidity
- SQL
- Statistical Programming
- Support Vector Machines
- Time-Series Analysis
- Truffle
- Validation
Earning Criteria
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To earn a certificate, participants are required to meet attendance requirements, complete graded assignments and challenges, and participate in group projects that they will display in a portfolio.
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Earners model future financial performance by creating a Jupyter Notebook, Google Colab Notebook, or Amazon SageMaker Notebook and prepare a training and testing dataset. Alternatively, they may apply a dimensionality reduction technique to reduce input features or apply feature engineering to generate new features to train the model. They create one or more machine learning models, fit and evaluate data, and make predictions using new data.
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Earner built an Ethereum blockchain to show understanding in how transactions are validated on a distributed ledger. They also leveraged machine learning to determine lending preferences and how effectively a cluster of customers would produce interest.
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Earners develop a Jupyter notebook, Google Colab notebook, Amazon SageMaker Studio notebook, or Streamlit application and one or more Python modules, machine learning models, or Solidity smart contracts. They document software version control, including creating and organizing a GitHub repository with complete README.md files. Project teams deliver presentations that include project goals, relevant code, conclusions, recommendations, and visualization of results and analysis.